About the Company
Our client is an emerging health technology company using AI to modernise digital care and pharmacy infrastructure. Our platform connects clinical operations with intelligent, patient-focused experiences - removing friction, improving coordination, and enabling more personalised care at scale.
Building a collaborative, mission-driven team that values creativity, ownership, and innovation. You’ll join at a formative stage, helping define both our AI systems and the engineering culture that powers them.
The Opportunity
As a Senior AI Engineer, you’ll lead the design and delivery of production-grade AI solutions that drive real business value. This is a hands-on, end-to-end role - from architecture and model development to deployment and optimisation.
You’ll work closely with product, engineering, and operations teams (and occasionally with enterprise clients) to identify opportunities, translate needs into scalable AI solutions, and bring models into production.
What You’ll Do
* Design and deploy AI systems across areas like personalisation, forecasting, and information retrieval
* Build and maintain robust data pipelines, model training workflows, and monitoring systems
* Collaborate cross-functionally to apply ML/AI to real-world business problems
* Develop tooling and automation for CI/CD, model serving, and A/B testing
* Prototype quickly and scale successful experiments into production-ready systems
What You’ll Bring
* 6+ years of software engineering experience
* 4+ years building and deploying ML/AI models in production
* Proficiency in Python (pandas, scikit-learn, PyTorch, etc.)
* Experience with modern backend stacks (TypeScript, Node.js, Go, or similar)
* Strong understanding of ML principles and model evaluation
* Experience with cloud-based model deployment (GCP preferred)
* Familiarity with containerised workflows (Docker, serverless) and MLOps tools (MLflow, Vertex AI, SageMaker)
* Excellent communication and collaboration skills in a remote-first team
* Willingness to travel occasionally for in-person collaboration or client work
Nice to Have
* Experience with retrieval-augmented generation (RAG) or foundation models
* Exposure to NLP, recommendation systems, or time series forecasting
* Familiarity with streaming architectures and experimentation platforms
* Understanding of healthcare data standards (HIPAA, FHIR)
* Interest in ethical AI and explainability